tbuckley/cabot-search huggingface dataset:
Small cell lung cancer: Novel treatments beyond immunotherapy
Authors: Job-Joris Meijer, Alessandro Leonetti, Giulia Airò, Marcello Tiseo, Christian Rolfo, Elisa Giovannetti, Mahrou Vahabi
Journal: Seminars in Cancer Biology (2022)

Small cell lung cancer (SCLC) arises in peribronchial locations and infiltrates the bronchial submucosa, including about 15% of lung cancer cases. Despite decades of research, the prognosis for SCLC patients remains poor because this tumor is characterized by an exceptionally high proliferative rate, strong tendency for early widespread metastasis and acquired chemoresistance. Omics profiling revealed that SCLC harbor extensive chromosomal rearrangements and a very high mutation burden. This led to the development of immune-checkpoint inhibitors as single agents or in combination with chemotherapy, which however resulted in a prolonged benefit only for a small subset of patients. Thus, the present review discusses the rationale and limitations of immunotherapeutic approaches, presenting the current biological understanding of aberrant signaling pathways that might be exploited with new potential treatments. In particular, new agents targeting DNA damage repair, cell cycle checkpoint, and apoptosis pathways showed several promising results in different preclinical models. Epigenetic alterations, gene amplifications and mutations can act as biomarkers in this context. Future research and improved clinical outcome for SCLC patients will depend on the integration between these omics and pharmacological studies with clinical translational research, in order to identify specific predictive biomarkers that will be hopefully validated using clinical trials with biomarker-selected targeted treatments.
Impact of HIV on Anal Squamous Cell Carcinoma Rates in the United States, 2001-2015
Authors: Elizabeth R Zhang, Ruth M Pfeiffer, April Austin, Megan A Clarke, Jennifer Hayes, Marie-Josèphe Horner, Analise Monterosso, Karen S Pawlish, Eric A Engels, Meredith S Shiels
Journal: JNCI Journal of the National Cancer Institute (2022)

Incidence of anal squamous cell carcinoma (SCC) has increased in the United States. People living with HIV (PLWH) have an elevated risk of anal SCC, and changes in the number of anal SCCs among PLWH may have influenced general population trends.Data were obtained from a linkage of HIV and cancer registries in 12 US regions. The proportion of anal SCCs occurring among PLWH was estimated by sex, age group, and race and ethnicity. To assess the impact of anal SCCs among PLWH on general population trends, annual percent changes (APCs) in incidence rates including and excluding anal SCCs among PLWH were estimated.Between 2001 and 2015, 14.5% of 16 110 anal SCC diagnoses occurred in PLWH. In 2013-2015, 35% of anal SCCs among men occurred in PLWH, but only 2% among women. The proportion of anal SCCs among PLWH was highest among 20- to 49-year-olds and Black and Hispanic individuals. General population anal SCC trends among men were strongly influenced by anal SCCs among PLWH: rates increased 4.6%/y (95% confidence interval [CI] = 1.4% to 8.0%) from 2001 to 2009 followed by a statistically non-significant decline (APC = -2.7%/y, 95% CI = -7.1% to 2.0%) from 2009 to 2015, but without anal SCCs among PLWH, rates were stable (APC = 0.7%/y, 95% CI = -0.8% to 2.3%). Anal SCC rates among women increased 3.8%/y (95% CI = 3.2% to 4.4%) during 2001-2012 and then declined statistically non-significantly (APC = -3.8%/y, 95% CI = -6.9% to -0.6%), and anal SCCs among PLWH had little impact on these trends.During 2001-2015, anal SCCs among PLWH contributed strongly to changes in incidence trends in the general US population among men, but not women.
Dorzagliatin add-on therapy to metformin in patients with type 2 diabetes: a randomized, double-blind, placebo-controlled phase 3 trial
Authors: Wenying Yang, Dalong Zhu, Shenglian Gan, Xiaolin Dong, Junping Su, Wenhui Li, Hongwei Jiang, Wenjuan Zhao, Minxiu Yao, Weihong Song, Yibing Lu, Xiuzhen Zhang, Huifang Li, Guixia Wang, Wei Qiu, Guoyue Yuan, Jianhua Ma, Wei Li, Ziling Li, Xiaoyue Wang, Jiao’e Zeng, Zhou Yang, Jingdong Liu, Yongqian Liang, Song Lu, Huili Zhang, Hui Liu, Ping Liu, Kuanlu Fan, Xiaozhen Jiang, Yufeng Li, Qing Su, Tao Ning, Huiwen Tan, Zhenmei An, Zhaoshun Jiang, Lijun Liu, Zunhai Zhou, Qiu Zhang, Xuefeng Li, Zhongyan Shan, Yaoming Xue, Hong Mao, Lixin Shi, Shandong Ye, Xiaomei Zhang, Jiao Sun, Ping Li, Tao Yang, Feng Li, Jingna Lin, Zhinong Zhang, Ying Zhao, Ruonan Li, Xiaohui Guo, Qi Yao, Weiping Lu, Shen Qu, Hongmei Li, Liling Tan, Wenbo Wang, Yongli Yao, Daoxiong Chen, Yulan Li, Jialin Gao, Wen Hu, Xiaoqiang Fei, Tianfeng Wu, Song Dong, Wenlong Jin, Chenzhong Li, Dong Zhao, Bo Feng, Yu Zhao, Yi Zhang, Xiaoying Li, Li Chen
Journal: Nature Medicine (2022)

Metformin, the first-line therapy for type 2 diabetes (T2D), decreases hepatic glucose production and reduces fasting plasma glucose levels. Dorzagliatin, a dual-acting orally bioavailable glucokinase activator targeting both the pancreas and liver glucokinase, decreases postprandial glucose in patients with T2D. In this randomized, double-blind, placebo-controlled phase 3 trial, the efficacy and safety of dorzagliatin as an add-on therapy to metformin were assessed in patients with T2D who had inadequate glycemic control using metformin alone. Eligible patients with T2D (n = 767) were randomly assigned to receive dorzagliatin or placebo (1:1 ratio) as an add-on to metformin (1,500 mg per day) for 24 weeks of double-blind treatment, followed by 28 weeks of open-label treatment with dorzagliatin for all patients. The primary efficacy endpoint was the change in glycated hemoglobin (HbA1c) levels from baseline to week 24, and safety was assessed throughout the trial. At week 24, the least-squares mean change from baseline in HbA1c (95% confidence interval (CI)) was -1.02% (-1.11, -0.93) in the dorzagliatin group and -0.36% (-0.45, -0.26) in the placebo group (estimated treatment difference, -0.66%; 95% CI: -0.79, -0.53; P < 0.0001). The incidence of adverse events was similar between groups. There were no severe hypoglycemia events or drug-related serious adverse events in the dorzagliatin and metformin combined therapy group. In patients with T2D who experienced inadequate glycemic control with metformin alone, dorzagliatin resulted in effective glycemic control with good tolerability and safety profile ( NCT03141073 ).
The natural history of peanut and egg allergy in children up to age 6 years in the HealthNuts population-based longitudinal study
Authors: Rachel L. Peters, Imma Guarnieri, Mimi L.K. Tang, Adrian J. Lowe, Shyamali C. Dharmage, Kirsten P. Perrett, Lyle C. Gurrin, Jennifer J. Koplin
Journal: Journal of Allergy and Clinical Immunology (2022)
Stepwise GATA1 and SMC3 mutations alter megakaryocyte differentiation in a Down syndrome leukemia model
Authors: Brahim Arkoun, Elie Robert, Fabien Boudia, Stefania Mazzi, Virginie Dufour, Aurélie Siret, Yasmine Mammasse, Zakia Aid, Matthieu Vieira, Imanci Aygun, Marine Aglave, Marie Cambot, Rachel Petermann, Sylvie Souquere, Philippe Rameau, Cyril Catelain, Romain Diot, Gérard Tachdjian, Olivier Hermine, Nathalie Droin, Najet Debili, Isabelle Plo, Sébastien Malinge, Eric Soler, Hana Raslova, Thomas Mercher, William Vainchenker
Journal: Journal of Clinical Investigation (2022)

Acute megakaryoblastic leukemia of Down syndrome (DS-AMKL) is a model of clonal evolution from a preleukemic transient myeloproliferative disorder requiring both a trisomy 21 (T21) and a GATA1s mutation to a leukemia driven by additional driver mutations. We modeled the megakaryocyte differentiation defect through stepwise gene editing of GATA1s, SMC3+/–, and MPLW515K, providing 20 different T21 or disomy 21 (D21) induced pluripotent stem cell (iPSC) clones. GATA1s profoundly reshaped iPSC-derived hematopoietic architecture with gradual myeloid-to-megakaryocyte shift and megakaryocyte differentiation alteration upon addition of SMC3 and MPL mutations. Transcriptional, chromatin accessibility, and GATA1-binding data showed alteration of essential megakaryocyte differentiation genes, including NFE2 downregulation that was associated with loss of GATA1s binding and functionally involved in megakaryocyte differentiation blockage. T21 enhanced the proliferative phenotype, reproducing the cellular and molecular abnormalities of DS-AMKL. Our study provides an array of human cell–based models revealing individual contributions of different mutations to DS-AMKL differentiation blockage, a major determinant of leukemic progression.
A potent PGK1 antagonist reveals PGK1 regulates the production of IL-1β and IL-6
Authors: Liping Liao, Wenzhen Dang, Tingting Lin, Jinghua Yu, Tonghai Liu, Wen Li, Senhao Xiao, Lei Feng, Jing Huang, Rong Fu, Jiacheng Li, Liping Liu, Mingchen Wang, Hongru Tao, Hualiang Jiang, Kaixian Chen, Xingxing Diao, Bing Zhou, Xiaoyan Shen, Cheng Luo
Journal: Acta Pharmaceutica Sinica B (2022)

Glycolytic metabolism enzymes have been implicated in the immunometabolism field through changes in metabolic status. PGK1 is a catalytic enzyme in the glycolytic pathway. Here, we set up a high-throughput screen platform to identify PGK1 inhibitors. DC-PGKI is an ATP-competitive inhibitor of PGK1 with an affinity of Kd = 99.08 nmol/L. DC-PGKI stabilizes PGK1 in vitro and in vivo, and suppresses both glycolytic activity and the kinase function of PGK1. In addition, DC-PGKI unveils that PGK1 regulates production of IL-1β and IL-6 in LPS-stimulated macrophages. Mechanistically, inhibition of PGK1 with DC-PGKI results in NRF2 (nuclear factor-erythroid factor 2-related factor 2, NFE2L2) accumulation, then NRF2 translocates to the nucleus and binds to the proximity region of Il-1β and Il-6 genes, and inhibits LPS-induced expression of these genes. DC-PGKI ameliorates colitis in the dextran sulfate sodium (DSS)-induced colitis mouse model. These data support PGK1 as a regulator of macrophages and suggest potential utility of PGK1 inhibitors in the treatment of inflammatory bowel disease.
Metabolic reprogramming of the intestinal microbiome with functional bile acid changes underlie the development of NAFLD
Authors: Ekaterina Smirnova, Mark D. Muthiah, Nicole Narayan, Mohamad S. Siddiqui, Puneet Puri, Velimir A. Luketic, Melissa J. Contos, Michael Idowu, Jen‐Chieh Chuang, Andrew N. Billin, Ryan S. Huss, Robert P. Myers, Sherry Boyett, Mulugeta Seneshaw, Hae‐Ki Min, Faridodin Mirshahi, Arun J. Sanyal
Journal: Hepatology (2022)

Abstract Background and Aims Bile acids are hepatic metabolites and have many properties considered to be relevant to the pathophysiology of NAFLD. Circulating levels of the intestinal microbiome‐modified bile acid deoxycholate are increased in cirrhosis. Approach and Results To further elucidate the role of bile acids and intestinal microbiota linked to bile acids in progressively severe NAFLD, a multiomic study of feces including 16S rRNA sequencing, microbial transcriptomics and metabolomics was performed in a cohort with varying phenotypes of NAFLD. Several bile acids of microbial origin derived from deoxycholic acid (DCA) (glycodeoxycholate, 7‐ketodeoxycholic acid, dehydrocholic acid) increased with disease activity and fibrosis stage. These were linked to increased expression of microbial bile salt hydrolase, bile acid operon (BaiCD) and hydroxysteroid dehydrogenases (hdhA) required for DCA and downstream metabolite synthesis providing a mechanistic basis for altered bile acid profiles with disease progression. Bacteroidetes and several genera of Lachnospiraceae family containing DCA generating genes increased with increasing disease severity, whereas several potentially beneficial microbes sensitive to antibacterial effects of DCA e.g., Ruminococcaceae were decreased. The clinical relevance of these data was confirmed in an independent cohort enrolled in a clinical trial for NASH where at entry DCA and its conjugates were associated with advanced fibrosis. In patients treated with placebo, DCA declined in those with fibrosis regression and increased in those with fibrosis progression. DCA rose further in those with compensated cirrhosis when they experienced decompensation. Conclusions These findings demonstrate a role for bile acids and the bile acid dependent microbiome in the development and progression of NAFLD and set the stage to leverage these findings for NASH biomarker development and for therapeutics.
Feasibility and safety of intranasally administered mesenchymal stromal cells after perinatal arterial ischaemic stroke in the Netherlands (PASSIoN): a first-in-human, open-label intervention study
Authors: Lisanne M Baak, Nienke Wagenaar, Niek E van der Aa, Floris Groenendaal, Jeroen Dudink, Maria Luisa Tataranno, Ubah Mahamuud, Cornelia H Verhage, Rian M J C Eijsermans, Liesbeth S Smit, Reint K Jellema, Timo R de Haan, Hendrik J ter Horst, Willem P de Boode, Sylke J Steggerda, Henk-Jan Prins, Colin G de Haar, Linda S de Vries, Frank van Bel, Cobi J Heijnen, Cora H Nijboer, Manon J N L Benders
Journal: The Lancet Neurology (2022)
Increased Reach and Effectiveness With a Low-Burden Point-of-Care Tobacco Treatment Program in Cancer Clinics
Authors: Alex T. Ramsey, Timothy B. Baker, Faith Stoneking, Nina Smock, Jingling Chen, Giang Pham, Aimee S. James, Graham A. Colditz, Ramaswamy Govindan, Laura J. Bierut, Li-Shiun Chen
Journal: Journal of the National Comprehensive Cancer Network (2022)

Background: Tobacco cessation after a cancer diagnosis can extend patient survival by improving outcomes for primary cancer and preventing secondary cancers. However, smoking is often unaddressed in cancer care, highlighting the need for strategies to increase treatment reach and cessation. This study examined a low-burden, point-of-care tobacco treatment program (ELEVATE) featuring an electronic health record–enabled smoking module and decision support tools to increase the reach and effectiveness of evidence-based smoking cessation treatment. Methods: This study included adult outpatient tobacco smokers (n=13,651) in medical oncology, internal medicine, and surgical oncology clinics from a large midwestern healthcare system. We examined reach and effectiveness of ELEVATE with 2 comparisons: (1) preimplementation versus postimplementation of ELEVATE and (2) ELEVATE versus usual care. Data were evaluated during 2 time periods: preimplementation (January through May 2018) and postimplementation (June through December 2018), with smoking cessation assessed at the last follow-up outpatient encounter during the 6 months after these periods. Results: The proportion of current tobacco smokers receiving cessation treatment increased from pre-ELEVATE to post-ELEVATE (1.6%–27.9%; difference, 26.3%; relative risk, 16.9 [95% CI, 9.8–29.2]; P &lt;.001). Compared with 27.9% treatment reach with ELEVATE in the postimplementation time period, reach within usual care clinics ranged from 11.8% to 12.0% during this same period. The proportion of tobacco smokers who subsequently achieved cessation increased significantly from pre-ELEVATE to post-ELEVATE (12.0% vs 17.2%; difference, 5.2%; relative risk, 1.3 [95% CI, 1.1–1.5]; P =.002). Compared with 17.2% smoking cessation with ELEVATE in the postimplementation time period, achievement of cessation within usual care clinics ranged from 8.2% to 9.9% during this same period. Conclusions: A low-burden, point-of-care tobacco treatment strategy increased tobacco treatment and cessation, thereby improving access to and the impact of evidence-based cessation treatment. Using implementation strategies to embed tobacco treatment in every healthcare encounter promises to engage more smokers in evidence-based treatment and facilitate smoking cessation, thereby improving care cancer for patients who smoke.
Abstract B009: Integrating mathematical modelling and wet-lab experiments to examine the scope for adaptive treatment scheduling of PARP inhibitors in ovarian cancer
Authors: Maximilian Strobl, Mehdi Damaghi, Alexandra Martin, Samantha Byrne, Mark Robertson-Tessi, Robert Gatenby, Robert Wenham, Philip Maini, Alexander R.A. Anderson
Journal: Cancer Research (2022)

Abstract PARP inhibitors (PARPis) represent a great advancement in the treatment of ovarian cancer, yet these drugs often fail after a few months due to emerging drug resistance. A recent clinical trial in prostate cancer showed that evolutionary-inspired, adaptive drug scheduling significantly delayed time to progression. This approach adaptively skipped treatment to maintain a pool of drug-sensitive cells that suppressed resistant cells through competition. Here, we present results from a combined modelling and experimental study in which we investigated whether adaptive therapy could delay resistance to the PARPi olaparib in ovarian cancer.We performed a series of in vitro experiments in which we used Incucyte Zoom time-lapse microscopy to characterize the cell population dynamics under different PARPi schedules. Leveraging these data we developed an ordinary differential equation mathematical model of treatment response, and used this model to test different plausible adaptive treatment schedules. Our model can accurately predict the in vitro treatment dynamics, even to new schedules, and suggests that treatment modifications need to be carefully timed, or one risks losing control over tumor growth, even in the absence of any resistance. This is because multiple rounds of cell division are required for cells to acquire sufficient DNA damage to induce apoptosis. As a result, adaptive therapy algorithms that modulate treatment but never completely withdraw it are predicted to perform better in this setting than strategies based on treatment interruptions. Subsequent experiments confirm this prediction in vivo. To conclude, we present preliminary work aiming at investigating the scope for clinical translation of our results by confronting our model with longitudinal CA-125 data from 53 ovarian cancer patients receiving olaparib at Moffitt. Overall, this study contributes to a better understanding of the impact of scheduling on treatment outcome for PARPis, and showcases some of challenges involved in developing adaptive therapies for new treatment settings. Citation Format: Maximilian Strobl, Mehdi Damaghi, Alexandra Martin, Samantha Byrne, Mark Robertson-Tessi, Robert Gatenby, Robert Wenham, Philip Maini, Alexander R.A. Anderson. Integrating mathematical modelling and wet-lab experiments to examine the scope for adaptive treatment scheduling of PARP inhibitors in ovarian cancer [abstract]. In: Proceedings of the AACR Special Conference on the Evolutionary Dynamics in Carcinogenesis and Response to Therapy; 2022 Mar 14-17. Philadelphia (PA): AACR; Cancer Res 2022;82(10 Suppl):Abstract nr B009.
Neuronal Ceroid Lipofuscinosis Owing to Complete Maternal Uniparental Disomy
Authors: Wenfei Yu, Lili Cao, Pengfei Lin
Journal: JAMA Neurology (2022)

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COVID-19 and Risk of Oxygen-Dependent Chronic Respiratory Failure: A National Cohort Study
Authors: Josefin Sundh, Magnus Ekström, Andreas Palm, Mirjam Ljunggren, Össur Ingi Emilsson, Ludger Grote, Sara Cajander, Huiqi Li, Fredrik Nyberg
Journal: American Journal of Respiratory and Critical Care Medicine (2022)
Abstract B016: Selection and reprogramming contribute to the evolution of targeted therapy resistance
Authors: Robert Vander Velde, Sydney Shaffer
Journal: Cancer Research (2022)

Abstract Targeted therapies provide substantial benefits to cancer patients by shrinking and controlling tumors. However, the long-term efficacy of targeted therapy is limited by the development of resistance. Once a tumor is fully resistant, it continues to grow despite the presence of the targeted therapy, leading to disease relapse in the patient. When the therapy is first applied, a number of studies have now shown that there is initially a selection for cells that are able to tolerate the drug (termed “tolerant cells”). This contrasts with selection of fully resistant cells. More recently our studies have suggested that the transition from tolerance to resistance is not binary and involves multiple changes. These changes can be propelled by the stochastic generation of heritable heterogeneity followed by selection (Darwinian evolution), by long-term changes in signaling networks (reprogramming) and by combinations of these two. The contribution of these factors determines the usefulness of strategies using either evolutionary dynamics (such as reducing population size or changing selective pressures on tumor cells) or therapies that alter cell states (such as inhibiting or activating key signaling nodes). We are using colony assays and developing barcoding techniques to address the role of selection and clonality in the evolution of full resistance to BRAF inhibitors in melanoma from a tolerant state. Early results show a rapid increase in fitness (relative to surviving tolerant cells) suggesting a role for selection immediately after the first selective event. These changes are followed by slow changes that may be the result of mostly reprogramming. This implies that strategies that manipulate evolutionary dynamics are most effective early in resistance evolution while later changes can be manipulated by altering signaling nodes. Citation Format: Robert Vander Velde, Sydney Shaffer. Selection and reprogramming contribute to the evolution of targeted therapy resistance [abstract]. In: Proceedings of the AACR Special Conference on the Evolutionary Dynamics in Carcinogenesis and Response to Therapy; 2022 Mar 14-17. Philadelphia (PA): AACR; Cancer Res 2022;82(10 Suppl):Abstract nr B016.
Capsid Inhibition with Lenacapavir in Multidrug-Resistant HIV-1 Infection
Authors: Sorana Segal-Maurer, Edwin DeJesus, Hans-Jurgen Stellbrink, Antonella Castagna, Gary J. Richmond, Gary I. Sinclair, Krittaecho Siripassorn, Peter J. Ruane, Mezgebe Berhe, Hui Wang, Nicolas A. Margot, Hadas Dvory-Sobol, Robert H. Hyland, Diana M. Brainard, Martin S. Rhee, Jared M. Baeten, Jean-Michel Molina
Journal: New England Journal of Medicine (2022)

Patients with multidrug-resistant human immunodeficiency virus type 1 (HIV-1) infection have limited treatment options. Lenacapavir is a first-in-class capsid inhibitor that showed substantial antiviral activity in a phase 1b study.
Integration of Face-to-Face Screening With Real-time Machine Learning to Predict Risk of Suicide Among Adults
Authors: Drew Wilimitis, Robert W. Turer, Michael Ripperger, Allison B. McCoy, Sarah H. Sperry, Elliot M. Fielstein, Troy Kurz, Colin G. Walsh
Journal: JAMA Network Open (2022)

Understanding the differences and potential synergies between traditional clinician assessment and automated machine learning might enable more accurate and useful suicide risk detection.